POS0095 SINGLE-CELL LANDSCAPE OF CD4+ T LYMPHOCYTES REVEALS A POTENTIAL ROLE OF CYTOTOXIC CELLS IN GIANT CELL ARTERITIS
Authors: E. Carmona, J. L. Callejas-Rubio, N. Ortego, E. Raya, R. Ríos Fernández, B. Timmermann, J. Martin Ibanez, A. Márquez
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> Giant cell arteritis (GCA) is a systemic vasculitis mediated by an aberrant immunological response against the endothelium of medium- and large-sized blood vessels [1]. Even though the pathogenic mechanisms that drive GCA are yet to be settled, there is strong evidence that CD4<sup>+</sup> T lymphocytes play a crucial role in the development of this vasculitis [2]. Recently, single-cell RNA sequencing has resulted in a scientific and technological revolution, enabling the characterization of the gene expression profile of thousands of individual cells in different tissues [3]. This approach has allowed the identification of new cell subtypes, some of them being exclusively represented in pathogenesis, and has also proved useful as a tool for reporting new disease-specific biomarkers. <h3>Objectives</h3> In this study, we aimed to define new pathological mechanisms driving GCA through the comprehensive characterization of the gene expression profile of CD4<sup>+</sup> T cells by performing single-cell RNA sequencing in GCA patients and healthy controls. <h3>Methods</h3> CD4<sup>+</sup> T cells from whole blood of 16 individuals (eight GCA patients and eight sex- and age-matched healthy controls) were obtained. Based on clinical parameters, five patients were classified as active GCA and 3 of them as patients in remission. Single-cell libraries were prepared from isolated CD4<sup>+</sup> T cells using the '<i>Chromium Single Cell Gene Expression'</i> (10X Genomics). Sequencing data were pre-processed with the CellRangerV3.0 software. Then, quality control analysis, dimensionality reduction, clustering and differential gene expression profiling were conducted with the R package Seurat V4[4]. <h3>Results</h3> A total of 114.799 cells were analyzed and classified into 13 clusters according to their transcriptomic profile. Manual annotation of the different clusters based on canonical markers permitted the identification of 6 distinct CD4<sup>+</sup> T cell types including naïve (Tnaïve), central memory (T<sub>CM</sub>), effector memory (T<sub>EM</sub>), effector memory expressing granzyme K (T<sub>EM</sub><i>GZMK</i><sup><i>+</i></sup>), regulatory (Tregs) and cytotoxic T lymphocytes (CTL). The comparative analysis of cell type composition between the different subgroups showed a significant reduction of the cytotoxic cell compartment in GCA patients in remission compared with active patients (p=0.011) and controls (p=0.045) as well as a decreased frequency of Tregs in active patients compared with healthy individuals (p=0.029). In addition, differential expression analysis evidenced a significant overexpression of granzyme B (<i>GZMB</i>) and the zinc finger protein 683 (<i>HOBIT),</i> both involved in cytotoxic processes, in CTLs of active patients compared with patients in remission (p=0.017) and controls (p=1.14x10-49), respectively. Moreover, in both active and in remission patients, the Treg compartment showed a reduced expression of genes related to regulatory functions, like <i>HLA-DRA</i> (p=3.34x10-7) and <i>LGALS1</i> (p=1.14x10-8), compared with healthy controls. <h3>Conclusion</h3> The first single-cell atlas of CD4<sup>+</sup> T cells in GCA provided evidence for the first time of a potential pathogenic role of CD4<sup>+</sup> T cells with cytotoxic functions in this vasculitis and supported the crucial role of Tregs in the pathogenesis of GCA. <h3>References</h3> [1]Jennette JC et al. 2012 Revised International Chapel Hill consensus conference nomenclature of vasculitides. Arthritis Rheum 2013. [2]Robinette ML. The Immunopathology of Giant Cell Arteritis Across Disease Spectra. Front Immunol 2021. [3]Cheung P et al. Single-cell technologies — studying rheumatic diseases one cell at a time. Nat Rev Rheumatol 2019. [4]Hao Y et al. Integrated analysis of multimodal single-cell data. Cell 2021. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> None Declared.